1. Field of the Invention
The present invention relates generally to ranking lists of data items, and more particularly to ranking lists of data items using inductively learned rules.
2. Background Art
Numerous applications require the examination of a large amount of data to isolate a relatively small number of events that can be subject to further analysis. Fraud detection in transactions including credit card transactions, fraud detection in corporate accounting activity, customer pattern identification using purchase records, extracting security information based on surveillance records, etc., are some of the applications that subscribe to a model of sifting through a large amount of data to isolate and further analyze a few highly suspect instances.
In an application for fraud detection that uses records of credit card transactions, for example, hundreds of millions of transaction records may be available in a predetermined format that is amenable to processing by a computer. In general, only a relatively small number of transactions are fraudulent. However, often there is no clear criteria by which fraud can be detected with certainty. Often, what is required is a deeper analysis of customer transaction patterns and other related factors, and such deeper analysis is practical only after a relatively small subset of transaction records are identified as possibly fraudulent.
Manually ranking such a large amount of data is tedious, error-prone and cost-prohibitive. Automated ranking using computer-implemented methods, e.g. neural networks and support vector machines, are available, but models generated using these methods are not human understandable, which often is a key requirement in many applications. Among all classification/ranking models, rules are the most human understandable. Rule induction algorithms have been successfully applied to many classification problems, but rules are generally not used for ranking.
Therefore, effective methods, systems and computer program products for automated ranking of data records using rules are needed.